Tag Archives: geospatial analysis

Employment by Occupation by Census Tract; 5-Year Trends

.. data and tools to examine patterns of employment by occupation by census tract and 5-year change .. the U.S. civilian employed population increased from 142.9 million in 2012 to 155.1 million in 2017, an increase of 12.1 million (8.5%) based on the American Community Survey (ACS) 1-year estimates. See this table to see how the employed population were distributed by occupation in 2012, 2017 and the 5-year change. How did your neighborhoods or market/service areas of interest change over the past 5 years? How will occupational employment patterns by tract/neighborhood change between now and 2023?

Patterns of Percent Employed in Health Occupations by Census Tract
The following graphic shows patterns of the employed population in health occupations as a percent of total civilian employed population ages 16 and over in the Minneapolis-St. Paul metro. This view uses the occupational category MBSA40 Healthcare practitioners and technical listed in scroll section below. Tracts with blue or green pattern exceed the national average as shown in national table. Click graphic for larger view, more detail (shows schools layer) and legend color/data intervals. This map illustrates the geographic level of detail available using census tract demographics and the relative ease to gain insights using geospatial data analytics tools. View related graphic showing tract with the largest employment in the “Healthcare practitioners and technical” occupational group among all tracts.

– View developed using CV XE GIS and related GIS project.

Drill-down to Census Tract Level
Examining patterns of employment by occupation, for the same scope of subject matter, at the sub-county level can provide more insights. What is the size of the employment for a selected occupation in a neighborhood or market/service area of interest? How has the size of an occupational group by census tract changed over the past five years? How do these patterns rank/compare by tract in a particular state, metro or county? Data on employment by occupational category from the Federal statistical system on a U.S. national scale for counties, cities and census tracts are only available from the American Community Survey (ACS).

Use tools, resources and methods described here to access, integrate and analyze employment by occupation for the U.S. by census tract. Use the interactive table to view, query, rank, compare census tract occupational characteristics, patterns and trends. Data are based on the American Community Survey (ACS) 2017 5-year estimates.

Related sections with census tract interactive tables:
– General Demographics .. Social .. Economic .. Housing 

Current Estimates & Projections
ACS tract/small area estimates lag by four years or more between the current year and reference year. ACS does not produce current year annual estimates but estimates based on a 5-year period. The 2017 ACS estimates are centric to 2015. Use the ProximityOne annual tract estimates and projections 2010 through 2023 for current year (e.g., characteristics as of 2018) estimates and anticipated change 5 years ahead.

Using the Interactive Table
An example of using the interactive table to view, query, rank, compare census tract occupational characteristics, patterns and trends is shown by the graphic presented below. The table shows 6 columns of employment data for all tracts in Harris County, TX. The table is ranked on the ACS 2017 health occupations employment (MBSA40) column. Tract 48-201-312600 had largest ACS 2017 health employment of 1,078 among all tracts in the county. Compare to 2012 patterns. Use settings below table to develop a similar view your geography and occupations of interest.

Occupational Categories
The interactive table includes occupational categories listed below.
Total population
Total Civilian employed population 16 years and over
MBSA00 . Management, business, science, and arts
MBSA10 . . Management, business, and financial
MBSA11 . . . Management
MNSA12 . . . Business and financial operations
MBSA20 . . Computer, engineering, and science
MBSA21 . . . Computer and mathematical
MBSA22 . . . Architecture and engineering
MBSA23 . . . Life, physical, and social science
MBSA30 .. Education, legal, community service, arts, and media
MBSA31 … Community and social service
MBSA32 … Legal
MBSA34 … Education, training, and library
MBSA35 … Arts, design, entertainment, sports, and media
MBSA40 .. Healthcare practitioners and technical
MBSA41 … Health diagnosing & treating practitioners & other tech
MBSA42 … Health technologists and technicians
SVC00 . Service
SVC10 . . Healthcare support
SVC20 . . Protective service
SVC21 . . . Fire fighting/prevention & other protective services
SVC22 . . . Law enforcement workers including supervisors
SVC30 . . Food preparation and serving related
SVC40 . . Building and grounds cleaning and maintenance
SVC50 . . Personal care and service
SOF00 . Sales and office
SOF10 . . Sales and related
SOF20 . . Office and administrative support
NRC00 . Natural resources, construction, and maintenance
NRC10 . . Farming, fishing, and forestry
NRC20 . . Construction and extraction
NRC30 . . Installation, maintenance, and repair
PTM00 . Production, transportation, and material moving
PTM10 . . Transportation
PTM20 . . Material moving

Data Analytics Web Sessions
See these applications live/demoed. Run the applications on your own computer.
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Developing Geographic Relationship Data

.. tools and methods to build and use geographic relationship files … which census blocks or block groups intersect with one or a set of school attendance zones (SAZ)? How to determine which counties are touched by a metropolitan area? Which are contained within a metropolitan area? Which pipelines having selected attributes pass through water in a designated geographic extent? This section reviews use of the Shp2Shp tool and methods to develop a geographic relationship file by relating any two separate otherwise unrelated shapefiles. See relasted Web page for a more detiled review of using Shp2Shp.

As an example, use Shp2Shp to view/determine block groups intersecting with custom defined study/market/service area(s) … the only practical method of obtaining these codes for demographic-economic analysis.

– the custom defined polygon was created using the CV XE GIS AddShapes tool.

Many geodemographic analyses require knowing how geometries geospatially relate to other geometries. Examples include congressional/legislative redistricting, sales/service territory management and school district attendance zones.

The CV XE GIS Shape-to-Shape (Shp2Shp) relational analysis feature provides many geospatial processing operations useful to meet these needs. Shp2Shp determines geographic/spatial relationships of shapes in two shapefiles and provides information to the user about these relationships. Shp2Shp uses the DE-9IM topological model and provides an extended array of geographic and subject matter for the spatially related geometries. Sh2Shp helps users extend visual analysis of geographically based subject matter. Examples:
• county(s) that touch (are adjacent to) a specified county.
• block groups(s) that touch (are adjacent to) a specified block group.
• census blocks correspond to a specified school attendance zone.
• attributes of block groups crossed by a delivery route.

Block Groups that Touch a Selected Block Group
The following graphic illustrates the results of using the Shp2Shp tool to determine which block groups touch block group 48-85-030530-2 — a block group located within McKinney, TX. Shp2Shp determines which block groups touch this block group, then selects/depicts (crosshatch pattern) these block groups in the corresponding GIS map view.

Geographic Reference File
In the process, Shp2Shp creates a geographic relationship file as illustrated below. There are six block groups touching the specified block group. As shown in the above view, one of these block groups touches only at one point. The table below (derived from the XLS file output by Shp2Shp) shows six rows corresponding to the six touching block groups. The table contains two columns; column one corresponds to the field GEOID from Layer 1 (the output field as specified in edit box 1.2 in above graphic) and column 2 corresponds to the field GEOID from Layer 2 (the output field as specified in edit box 2.2 in above graphic). The Layer 1 column has a constant value because a query was set (geoid=’480850305302′) as shown in edit box 1.3. in the above graphic. Any field in the layer dataset could have been chosen. The GEOID may be used more often for subsequent steps using the GRF and further described below. It is coincidental that both layers/shapefiles have the field named “GEOID”.

Layer 1 Layer 2
480850305302 480850305272
480850305302 480850305281
480850305302 480850305301
480850305302 480850305311
480850305302 480850305271
480850305302 480850305312

Note that in the above example, only the geocodes are output for each geography/shape meeting the type of geospatial relationship. Any filed within either shapefile may be selected for output (e.g., name, demographic-economic field value, etc.)

How it Works — Shp2Shp Operations
The following graphic shows the settings used to develop the map view shown above.

See related section providing details on using the Shp2Shp tool.

Geographic Relationships Supported
The Select Relationships dropdown shown in the above graphic is used to determine what type of spatial relationship is to be used. Options include:
• Equality
• Disjoint
• Intersect
• Touch
• Overlap
• Cross
• Within
• Contains
See more about the DE-9IM topological model used by Shp2Shp.

Try it Yourself

See full details on how you can use any version, including the no fee versin, of CV XE GIS to use the Shp2Shp tools. Here are two examples what you can d. Use any of the geospatial relatoinships. Apply your own queries.

Using Touch Operation
Select the type of geographic operation as Touch. Click Find Matches button. The map view now shows as:

Using Contains Operation
Click RevertAll button. Select the type of geographic operation as Contains. Click Find Matches button. The map view now shows as:

Relating Census Block and School Attendance Zones
The graphic shown below illustrates census blocks intersecting with Joyner Elementary School attendance zone located in Guilford County Schools, NC (see district profile). The attendance zone is shown with bold blue boundary. Joyner ES SAZ intersecting blocks are shown with black boundaries and labeled with Census 2010 total population (item P0010001 as described in table below graphic). Joyner ES is shown with red marker in lower right.


– view developed using CV XE GIS and related GIS project; click graphic for larger view

See more about this application in this related Web section.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Relating Block Groups to ZIP Code Areas

.. the popularity of block group demographic data is mainly due to this being the smallest geographic area for which annually updated demographic data, with U.S. wall-to-wall coverage, are available from the American Community Survey (ACS) — or any other source. While block groups nest within census tracts from both a geometric and geocode hierarchy perspective, the relationship between block groups and ZIP code areas is far less clear. Analysts are often interested in relating block group geography and demographics with ZIP code areas. The Census 2010 217,740 block groups intersect with 32,824 ZIP code areas forming 308,805 BG-ZIP area combinations. This section reviews tools to examine the relationship between block group geography/demographics and ZIP code areas. See related Web section for full details.

Block Group 06-075-015700-1 in Context of ZIP Code Area 94115
Block groups (BGs) are often wholly contained within a ZIP code area. But around the ZIP code area boundary, intersecting block groups are often split by the ZIP code boundary. This relationship is illustrated in the graphic shown below. This graphic shows block group 06-075-015700-1 (yellow BG code label, cross-hatched, black boundary) in context of ZIP Code area 94115 (white labels, bold blue boundary) located in San Francisco. This GIS application is closely related to the Mapping Block Group Data, also uses the San Francisco area in applications.

– view developed with ProximityOne CV XE GIS and related GIS project.
– view all San Francisco ZIP code areas; see ZIP 94115 in context.

The cross-hatched BG 060750157001 (or 06-075-015700-1) is split by ZIP code 94115. What part of the BG is in ZIP code area 94115 and adjacent ZIP code area 94118? The situation is similar for BG 060750157002, directly below 060750157001, which is split into 3 ZIP code areas. Use the interactive table to make these determinations.

Using the Interactive Table
The interactive table illustrated in the graphic below contains a row for block group area part which intersects with a unique ZIP code area. The simple case of a BG being split into two ZIP code areas can be visually observed as shown in the graphic presented above. A tabular relational table offers processing advantages compared to visual geospatial depictions. Here is an example. ZIP code area 94115 contains whole or parts of 32 BGs. To view/verify this using the table below, 1) click the ShowAll button below the table, then 2) click the Find ZIP button (edit box at right preloaded with this ZIP). The table refreshes with 32 rows — the BGs intersecting with this ZIP code area. Verify there are 32 BGs; the BG codes can be viewed in column 1.

In the above map at the top of this section, block group 06-075-015700-1 is shown visually to be contained in two ZIP code areas. To view how block group 06-075-015700-1 is split among multiple ZIP code areas using the table below, 1) click the ShowAll button below the table, then 2) click the Find GEOID button (enter G0607501057001 in the edit box to right of Find GEOID then click Find button). The table refreshes with two BGs. In this example, it can be seen that the total BG population (Census 2010) is 1,375. The part of the BG population is shown and the percent of the population from that BG allocated to the corresponding ZIP code are shown. This BG has a total area 0.09 square miles. The part of the BG area Census 2010, square miles) is shown and the percent of the area from that BG allocated to the corresponding ZIP code are shown.

Use the main Web section interactive table to examine areas of interest. Join me in a Data Analytics Lab session to discuss use of these data using analytical tools and methods applied to your situation.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Business Data Analytics: Methods & Tools

Business Data Analytics can help most any business more effectively reach goals and objectives. Whether a new or established business, serving a county or national market, similar tools and methods apply. See related Web version for more details.

• How can you examine patterns/characteristics of existing customers?
• Where are prospective customers and possible unknown opportunities?
• How do you best define your market area?
  – what geographies have the largest number of prospects?
• What are the sales potential in this market area?
  – what are the best measures to examine sales potential?
• What is your competitive position?
  – how many other establishments offer a similar service in your market area?
• How can your sales data identify geographic areas of opportunity?

Tools and methods described here can help answer these questions and facilitate strategic planning. Here are key steps to using Business Data Analytics in your business. These applications make use of a GIS project and data for a business located in the San Diego area. Click link to view graphics.
Business locations
Territories served
Market characteristics
Urban population by block; population by tract
Customer locations
Prospect locations
Competitor locations
Composite of above
Related topics

Locations [goto top]
Where are the business locations/stores/operations
Blue triangle markers show existing locations. Are these the ideal locations?

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Territories Served [goto top]
What territories do locations serve? Are they developed correctly?
Territories for service/market areas are shown as color-shaded areas.
— flexibly re-define territories

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Market Characteristics [goto top]
What are the market characteristics?
Graphic shows patterns of median household income (MHI) by census tract;
— identifying areas with best opportunity
— examine wide-ranging demographic-economic characteristics
— market area tracts shown with cross-hatch pattern
— MHI intervsls/color correspondence shown in legend at left of map
— ranges can be customized/shifted to suit

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Urban Population by Block; Population by Tract [goto top]
Urban census blocks are shown with an orange fill pattern.
– examine scope of urban areas and how they relate to business development.
Census tract population is shown as a label for all tracts.
– identify population concentrations/attributes for small areas.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Customers [goto top]
Red markers show existing customers.
— linked to customer/product database

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Prospects [goto top]
Orange and green markers show prospects based on different sources/criteria.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Competitors [goto top]
What is the competitive position/where are competitors located?
Red triangle markers show where competitors are located.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Composite View [goto top]
Integrating business operating environment.
Graphic shows zoom-in to Encinatas location with all features shown separately in above views.
Roads/streets have been added; optionally use for routing and locational analysis.

— view created using CV XE GIS and associated Business Patterns GIS Project
— click graphic for larger showing details.

Related Topics for Extended Analysis [goto top]
These extended topics make use of the data and analyses reviewed above. These topics will be covered in subsequent sections.

• Determining performance relative to the market characteristics
• Assessing impact of external and internal factors affecting operations
  – supply chain, labor force, costs, demand …
• Examining financial situation and outlook?
• Determining areas of missed opportunity
  – metros, hot spots within metros (tracts)
• Using collective data in models for predictive analyses
  – how might things change, when where and how?
• How to interpret statistical releases
  – determining which relevant, assessing implications for impact
• How to most effectively make team/collaborative/management decisions

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.